Accurate predictions of SARS-CoV-2 infectivity from comprehensive analysis.

An unprecedented amount of SARS-CoV-2 data has been accumulated compared with previous infectious diseases, enabling insights into its evolutionary process and more thorough analyses. This study investigates SARS-CoV-2 features as it evolved to evaluate its infectivity. We examined viral sequences and identified the polarity of amino acids in the receptor binding motif (RBM) region.

Association between Socioecological Status, Nutrient Intake, and Cancer Screening Behaviors in Adults Aged 40 and Over: Insights from the Eighth Korea National Health and Nutrition Examination Survey (KNHANES, 2019).

Cancer screening is pivotal for early detection and improved survival rates. While socio-ecological factors are known to influence screening uptake, the role of lifestyle, dietary habits, and general health in shaping these decisions remains underexplored. Utilizing the 2019 Korea National Health and Nutrition Examination Survey (KNHANES), this study examined the myriad of factors impacting cancer screening utilization.

Investigating the Influence of Heavy Metals and Environmental Factors on Metabolic Syndrome Risk Based on Nutrient Intake: Machine Learning Analysis of Data from the Eighth Korea National Health and Nutrition Examination Survey (KNHANES).

This study delves into the complex interrelations among nutrient intake, environmental exposures (particularly to heavy metals), and metabolic syndrome. Utilizing data from the Korea National Health and Nutrition Examination Survey (KNHANES), machine learning techniques were applied to analyze associations in a cohort of 5719 participants, categorized into four distinct nutrient intake phenotypes. Our findings reveal that different nutrient intake patterns are associated with varying levels of heavy metal exposure and metabolic health outcomes.

Blood transcriptome differentiates clinical clusters for asthma.

Background: In previous studies, several asthma phenotypes were identified using clinical and demographic parameters. Transcriptional phenotypes were mainly identified using sputum and bronchial cells.

Objective: We aimed to investigate asthma phenotypes via clustering analysis using clinical variables and compare the transcription levels among clusters using gene expression profiling of the blood.

Association between household income levels and nutritional intake of allergic children under 6 years of age in Korea: 2019 Korea National Health and Nutrition Examination Survey and application of machine learning.

Introduction: This study investigated the prevalence of allergic diseases in Korean children aged 6 and below, focusing on the interplay between nutritional status, household income levels, and allergic disease occurrence.

Methods: This study used data from the 2019 Korea National Health and Nutrition Examination Survey, a nationwide comprehensive survey, and included a representative sample of 30,382 children under the age of 6 to investigate in detail the relationship between allergic diseases, nutritional intake, and socioeconomic factors. Logistic regression analysis was performed to identify factors associated with allergic diseases, including gender, BMI, eating habits, dietary supplement intake, and nutrient consumption.

Tunable Synthesis of Predominant Semi-Ionic and Covalent Fluorine Bonding States on a Graphene Surface.

In this study, fluorinated graphene (FG) was synthesized via a hydrothermal reaction. Graphene oxides (GOs) with different oxygen bonding states and oxygen contents (GO(F), GO(P), and GO(HU)) were used as starting materials. GO(F) and GO(P) are commercial-type GOs from Grapheneall.